Job Title: Machine Learning Engineer Company: YOTI Job Category: Machine Learning Roles & Responsibilities: More about the Team and the Role This role is part of our internal R\&D team, working on innovative projects in computer vision, deep learning, and face biometrics. Some of the work the team is doing includes developing our in\-house facial age estimation model, our facial anti\-spoofing models and other AI\-driven solutions. Working Arrangements: This will be a hybrid role and you will be expected to work from our Aldgate office atleast 1 day a week. Responsibilities * Build upon our existing preprocessing system to add functionality for new data modalities, and automation of data preprocessing tasks in Python and SQL. * Manage large scale datasets, ensuring data integrity, quality and usability for research initiatives. * Collaborate with research scientists to establish efficient experimentation and model training workflows. * Develop tools that accelerate experimentation and streamline research processes. * Support model evaluation conducting regression and performance tests to ensure model reliability and accuracy. * Monitor and troubleshoot data pipelines, ensuring smooth operation and timely delivery of research data. * Document data workflows, best practices, and technical solutions to ensure knowledge sharing and reproducibility. * Collaborate with product teams to identify and implement data\-driven solutions to business challenges. * Ensure compliance with data governance policies and security best practices. * Hybrid Working: Enjoy the best of both worlds with a blend of home working and time spent in our central London, dog\-friendly office. * Core Working Hours: We focus on outputs, not clock\-watching. Our core hours support the flexibility you need for a genuine work\-life balance. * Work from Anywhere: Want a change of scenery? Take advantage of our policy to work remotely from abroad for short periods. * Generous Annual Leave: 25 days holiday as standard, plus your Birthday Off to celebrate properly. * "Yotiversary" Days: Loyalty rewarded \- earn up to three additional paid days off based on your length of service. * Enhanced Parental Leave: We support growing families with up to six months’ fully paid maternity leave, 2 weeks of paid paternity leave plus a further four weeks of enhanced flexibility and time off, and enhanced parental provisions. Feel free to ask for more details! * Wellbeing Support: Access to trained, in\-house Mental Health First Aiders whenever you need a confidential chat, plus a fully comprehensive Employee Assistant Program. * Personal Development Budget: A dedicated, individual training budget to spend on your professional growth, plus quarterly YOTI Afternoons dedicated entirely to your professional development. * “Selfie Time": Paid time off every year to focus on volunteering, charity work, or personal passion projects. * Matched Fundraising: Double your impact \- we match charitable fundraising contributions made by our team. * Unpaid Sabbatical: Career breaks available for long\-term travel or personal resets after continuous service. This is a great opportunity to join a company that is leading the way for innovative and responsible identity verification. We’re looking for people who can adapt to a fast\-paced environment, as well as champion our brand and what we stand for. We value a positive attitude and people who have a collaborative, creative and transparent approach to solving problems. For more information about how we manage your data please read our Applicant Privacy Notice. Work Location: London, ENG, UK Availability: Full time

Job Title: Senior Software Engineer - Machine Learning Company: Liberty IT Job Category: Machine Learning Roles & Responsibilities: Reach beyond with Liberty IT; this is where you’ll find the challenges, where you’ll be given the scope and the support to go further, dig deeper and fly higher. This role is designed to give you meaningful opportunities to develop and broaden your Machine Learning, MLOps and cloud\-native engineering skills. You'll work on technology that enables critical business decisions across engineering groups, combining Python engineering, observability, cloud\-native technologies and modern front\-end development. * Strong experience developing high\-quality, maintainable software solutions using Python * Experience with observability and monitoring tools * Experience working with MLOps, model deployment, model governance, or machine learning platforms * Experience building modern web applications using JavaScript and React * Experience working with Kubernetes and cloud\-native technologies * Experience with DevOps tools, CI/CD and agile delivery * Experience collaborating with Product Owners, UX Designers and stakeholders We've included some further skills and experience that would be great. However, don't rule yourself out if you haven't had the opportunity to develop these yet. This role offers the support, learning and practical exposure to help you build them. * Be part of a team working to enhance platform and GUI experience * Develop maintainable Python code to expand platform capabilities * Build front\-end experiences using JavaScript and React * Use observability tools to improve reliability and UX * Contribute to Kubernetes\-based cloud\-native solutions * Champion code quality, testing and CI/CD * Write clean code in line with the team’s set standards and look for ways to improve them * Own, scope and deliver well\-defined deliverables or stories; communicate and update your progress regularly at stand\-ups or similar agile events * Mentor and guide more junior team members to deliver well\-defined features, functions or components In this role, you'll be supported to build capability across the machine learning engineering and MLOps lifecycle. You will have opportunities to: * Develop deeper expertise in Python for production ML platforms and services * Learn how models move from development into reliable, governed production environments * Build practical experience with MLOps, model deployment, model monitoring and model governance * Strengthen your understanding of observability and use monitoring insights to improve reliability and user experience * Gain hands\-on experience with Kubernetes, containers and cloud\-native architecture * Develop modern front\-end skills using JavaScript and React to create intuitive tools for technical and business users * Learn how platform design supports modellers, reviewers, data scientists and business stakeholders * Improve your DevOps, CI/CD, automated testing and production support skills * Work with emerging technologies and assess how they can be introduced safely into delivery lifecycles * Learn from experienced engineers through pairing, mentoring, code reviews and collaborative design * Take ownership of increasingly complex stories and platform capabilities as your skills develop Work Location: Belfast, NIR, UK Availability: Full time

Job Title: Full-Stack Software Engineer III Company: JPMorganChase Job Category: Machine Learning Roles & Responsibilities: JOB DESCRIPTION Join a team that is redefining how enterprise infrastructure technology is built, delivered, and scaled. At JPMorganChase, we invest in our engineers — giving you access to cutting\-edge tools, meaningful mentorship, and the opportunity to grow your career across one of the world's most complex and innovative technology organizations. Here, your work doesn't just support a product — it powers the infrastructure that keeps global markets moving. As a Software Engineer III at JPMorganChase within the Infrastructure Platforms, Data Center Services team, you serve as a seasoned member of an agile team that works to enhance, build, and deliver trusted market\-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. In this role, you will bring both technical depth and collaborative energy to a team that values quality, innovation, and continuous improvement. Job Responsibilities * Apply advanced technical skills to design, develop, and deliver full\-stack solutions across frontend (React) and backend (Node.js/TypeScript, Python) services * Create secure, high\-quality production code and maintain algorithms that run reliably and synchronously with appropriate systems * Produce architecture and design artifacts for complex application components, ensuring design constraints are met in implementation * Gather, analyze, synthesize, and develop visualizations from large data sets in support of continuous improvement of software applications * Proactively identify hidden problems and patterns in data, and use these insights to drive improvements to coding hygiene and system architecture * Develop subject matter expertise in a specific technical domain relevant to Data Center Services (e.g., UI/UX, backend architecture, software development lifecycle tooling, testing strategy, or operational support) * Contribute to software engineering communities of practice and employee resource groups through facilitation, guest speaking, or content contribution * Mentor junior software engineers and actively support their technical growth and development * Leverages enterprise\-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards * Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise\-authorized AI\-assisted development and automation capabilities, to improve the value realized by automation J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first\-class business in a first\-class way approach to serving clients drives everything we do. We strive to build trusted, long\-term partnerships to help our clients achieve their business objectives. Work Location: London, ENG, UK Availability: Full time

Job Title: Machine Learning Engineer Company: National Gas Job Category: Machine Learning Roles & Responsibilities: As Britain's national gas network, we help keep the lights on, businesses running, and homes warm by maintaining the critical infrastructure that transports gas across Great Britain. While providing the energy security Britain relies on today, we're also helping transform the network for a clean energy future. About the role ------------------ We're looking for a Machine Learning Engineer to build, deploy, monitor and maintain advanced analytics, forecasting and machine learning solutions that support the safe and efficient operation of Britain's gas transmission network. You'll take ownership of turning analytical models into robust operational products, ensuring they deliver long\-term value to the business. Data plays a critical role in how National Gas operates and plans for the future. From forecasting network demand and understanding weather impacts to optimising asset performance and operational decisions, you'll help ensure data science solutions are deployed, scalable, maintainable and trusted across the business. * Deploy, monitor and maintain forecasting, optimisation, machine learning and AI solutions in production environments. * Build and manage model monitoring, automated testing, deployment processes and operational support capabilities for machine learning and AI solutions. * Work closely with Data Scientists to productionise analytical models and ensure they remain reliable, scalable, supportable and aligned with operational requirements throughout their lifecycle. * Analyse and prepare large datasets from operational, asset, weather and market sources. * Support the development of forecasting, optimisation and machine learning models where required. * Create dashboards, visualisations and applications that communicate insights to stakeholders. * Work closely with engineers, operators and business teams to embed solutions into day\-to\-day operations. * Measure and demonstrate the value delivered by analytical solutions. What you'll bring --------------------- * Strong commercial experience as a Machine Learning Engineer, MLOps Engineer, Data Scientist or similar quantitative role. * Experience supporting the development, deployment or operation of forecasting, optimisation or machine learning models within a business environment. * Strong Python programming skills, including experience with libraries such as pandas and scikit\-learn. * Strong experience deploying, monitoring and maintaining machine learning or analytical solutions in production environments, including automated testing, model monitoring and version control. * Experience extracting, manipulating and analysing data using SQL. * Ability to communicate complex technical concepts clearly to both technical and non\-technical stakeholders. * Degree in a quantitative discipline such as Data Science, Mathematics, Engineering, Statistics, Computer Science or a related STEM subject, or equivalent industry experience. We're building a workforce that reflects the communities we serve, championing diversity, and creating an inclusive workplace where everyone is valued for their unique contribution. We support reasonable adjustments throughout the recruitment process and beyond. * Market\-leading double\-match pension (up to 12% company contribution) * Annual performance bonus up to 6% * Access to the Tusker salary sacrifice car scheme * 26 days holiday (plus statutory holidays) * 10x salary life assurance and income protection * Flexible benefits including healthcare, dental, and technology options * Family\-friendly policies, wellbeing support, and professional development opportunities Work Location: Warwick, ENG, UK Availability: Full time

Job Title: Senior MLOps Engineer Company: Elsevier Job Category: Machine Learning Roles & Responsibilities: About the role: As a Senior MLOps Engineer, you should be able to define the scope of a project with support of managers and execute that project independently. Individuals in this role can also support the development and training of junior staff. Senior Data Scientist I should be self\-sufficient in executing basic methods, and work within their teams to execute increasingly sophisticated approaches to deliver outcomes. They should also support the development of best practices. Key Responsibilities: * Maintain and version model registries and artifact stores to ensure reproducibility and governance * Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. * Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. * Design and implement the engineering components of GAR\+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self\-hosted * Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs * Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization * Partner with Subject\-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long\-term goals. A global leader in information and analytics, we help researchers and healthcare professionals’ advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1\-855\-833\-5120\. Work Location: London, ENG, UK Availability: Full time

Job Title: Head of Technical Program Management, Applied AI Company: Lilt- Lega Italiana per la Lotta contro i Tumori Job Category: Machine Learning Roles & Responsibilities: AI is changing how the world communicates — and LILT is leading that transformation. At LILT, we empower our teammates with leading tools, global collaboration, and growth opportunities to do their best work. Our company virtues—Work together, win together; Find a way or make one; Dance in the customer's shoes; Quicker than they expect; Quality is Job 1—guide everything we do. We are trusted by Intel Corporation, Canva, the United States Department of Defense, the United States Air Force, ASICS, and hundreds of global Enterprises. Backed by Sequoia, Intel Capital, and Redpoint, we’re building a category\-defining company in a $50B\+ global translation market being redefined by AI. ### About the Role As Head of Technical Program Management for Applied AI, you will drive and own all project execution, customer outcomes, and delivery excellence across LILT’s Applied AI practice for the world's leading AI labs. Serving as builder and coach, you will lead the people, operations, and systems behind every Applied AI engagement — multilingual and multimodal training data, evaluations, and benchmark programs — and make sure each one ships on time, on budget, and to the highest quality bar. You are responsible for constructing LILT’s technical program management capabilities from the ground up while actively developing, mentoring, and elevating a high\-performing team. Operating at the intersection of cutting\-edge AI research and industrial\-scale execution, you hold total accountability for every customer engagement —ensuring every deliverable across your entire team meets the highest standards of precision, speed, and technical rigour. This is an operator's role: you will balance high\-stakes operational ownership with a builder and coach mindset. You will manage and run a high\-volume, high\-velocity delivery organization: Technical Program Managers, project managers, and the expert and vendor workforces behind them. You bring equal passion to building the operational systems and cadence, capacity models, quality systems, and execution frameworks that power our AI lab deliverables, and coaching your team to operate as high\-agency "CEOs" of their respective customer portfolios, , all while staying close enough to the work to step into a critical program or a customer escalation when it matters. You are technically fluent enough to partner with researchers and engineers, but your edge is turning complex, ambiguous customer requirements into reliable, repeatable delivery. While you empower your team to drive day\-to\-day execution, the buck stops with you for overall portfolio health, customer retention, program SLAs, and delivery outcomes. ### Responsibilities * End\-to\-end Practice Ownership: Serve as the single point of accountability for customer outcomes across all Applied AI programs — technical delivery, project work and timelines, quality SLAs, margin, and customer satisfaction. You own top\-line program success metrics, quality SLAs, delivery timelines, and customer satisfaction across all Applied AI projects. * Lead and scale the delivery team: Recruit, mentor, and scale a world\-class team of TPMs and project managers. Set clear goals, coach for ownership, unblock across complex technical and operational challenges, and build a team that runs complex programs independently. * Run delivery operations and capacity planning at volume: Own capacity planning, staffing, and resource allocation across programs. Turn shifting customer demand into reliable production plans and delivery forecasts that protect speed and margin. * Build the delivery operating system: Standardize intake, scoping, kickoff, quality control, reporting, and close\-out. Turn individual program learnings into repeatable playbooks, systems, processes, and dashboards. * Strategic Customer Partnership \& Escalations: Act as executive partner and delivery sponsor for key frontier AI lab relationships. Proactively co\-develop benchmark transcreations with customer research leads. Lead escalations, run business reviews, and help shape scope, pricing, and timelines with Sales. * Own quality: Partner with Research to standardize quality control across delivery, including embedded calibration, gold sets, inter\-annotator agreement, LLM\-as\-a\-judge evaluation, model eval pipelines and root\-cause analysis into every customer program, ensuring that quality issues are proactively controlled and mitigated. * Manage the expert and vendor workforce: Work with Expert Supply and Operations to qualify, manage, and engage multilingual contributors and vendors, with clear performance and cost metrics. * Cross\-functional Workflow Design and Execution: Design, build, and optimize scalable program frameworks for text, image, video, and audio modalities. Turn complex technical requirements into seamless operational realities, bridging Sales, Engineering, Research, Product, Production, and Engineering to scope and build project workflows that are designed optimally, launched quickly, and executed smoothly * Accountable Mindset \& Ownership: Proven track record as the final owner of large\-scale, mission\-critical technical portfolios, with direct accountability for project delivery, customer outcomes, and SLA adherence. Demonstrated experience architecting mitigations for AI\-specific operational risks (e.g., dataset contamination, domain drift, quality decay, and SLA vulnerabilities). * Experience: 10\+ years in delivery, operations, or program leadership, including 5\+ years managing managers or multi\-team delivery organizations.Proven ownership of a large, customer\-facing delivery portfolio with accountability for SLAs, quality, and margin. * Builder \& Coach Mindset: Proven track record of building technical program functions, processes, and systems from scratch, coupled with a deep dedication to coaching, mentoring, and growing talent. * People Management \& Leadership: 5\+ years of direct people management experience building and scaling TPM, Product, or Engineering teams within high\-growth AI or enterprise tech environments. * Frontier AI Expertise: Deep, hands\-on understanding of the modern AI landscape—including LLMs, multimodal models, training/inference pipelines, and complex dataset diversity (multilingual and multi\-domain). Hands\-on experience delivering AI training data, human data, LLM evaluation, annotation, or localization programs at scale, with distributed contributor or vendor workforces. * 0\-to\-1 \& Scale Experience: Demonstrated ability to build operating systems in high\-velocity startup environments and scale them to support high\-throughput, mission\-critical operations where quality control is paramount. * Strong Data Fluency: comfortable using SQL, spreadsheets, or BI tools to run the business on metrics such as throughput, quality, cost per task, and utilization. * Contemporary Industry Acumen: Working knowledge of the modern AI landscape (LLMs, multimodal models, training and evaluation pipelines) to partner credibly with researchers and engineers. * Executive Stakeholder Management: Excellent business acumen, executive presence, and communication style with experience building high\-trust partnerships with top\-tier AI labs, customers, and enterprise executive teams * Education: B.S. or M.S. in Computer Science, AI, or a related technical field with 12\+ years of industry experience (or Ph.D. with 8\+ years). Work Location: London, ENG, UK Availability: Full time

Job Title: 2027 Software Dev Engineer Intern (Machine Learning) - UK Company: Amazon.com Job Category: Machine Learning Roles & Responsibilities: Our Software Development Engineer (SDE) interns use modern technology to solve complex problems while seeing their work's impact first\-hand. The challenges SDE interns solve at Amazon are meaningful and influence millions of customers, sellers, and products globally. We seek individuals passionate about creating new products, features, and services while managing ambiguity in an environment where development cycles are measured in weeks, not years. We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high\-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth. Amazon internships across all seasons are full\-time positions, and interns should expect to work in office, Monday\-Friday, up to 40 hours per week typically between 8am\-5pm. Specific team norms around working hours will be communicated by your manager. Interns should not have conflicts such as classes or other employment during the Amazon work\-day. Applicants should have a minimum of one quarter/semester/trimester remaining in their studies after their internship concludes. Key job responsibilities * Break down complex, ambiguous problems into well\-defined, solvable components before implementation. * Contribute to the design and development of scalable, reliable services, with distributed\-systems scope varying by team. * Use GenAI and AI\-powered tools to enhance development productivity, and critically validate, verify, and integrate AI\-generated code, exercising sound judgement about when to trust AI output. * Write clean, maintainable code following best practices and design patterns. * Work in an agile environment practicing CI/CD principles while participating in operational responsibilities including on\-call duties. * Demonstrate operational excellence through monitoring, troubleshooting, and resolving production issues. As an intern, you will be matched to a manager and a mentor and will have the opportunity to influence the evolution of Amazon technology and lead critical projects early in your career. In addition to working on an impactful project, you will have the opportunity to engage with Amazonians for both personal and professional development, expand your network, and participate in activities with other interns throughout your internship. No matter the location of your internship, we give you the tools to own your project and learn in a real\-world setting. As an Amazon Intern, you'll be part of a vibrant, supportive community that empowers your growth and development. You'll collaborate with interns from around the world, networking and participating in social events to broaden your perspectives. You can also join specialized groups focused on areas like sustainability to explore your diverse interests. Support: The internship program provides a robust support system, including weekly intern office hours, dedicated IT and HR support, and a program team committed to your success. This ensures you have the guidance and assistance needed to thrive. Exclusive learning sessions will further enhance your skills, granting you access to Amazon's cutting\-edge learning platforms and the expertise of industry leaders. These structured development opportunities will prepare you for the next step in your career. Work Location: London, ENG, UK Availability: Full time

Job Title: MLOps Engineer Company: Valarian Technologies Job Category: Machine Learning Roles & Responsibilities: London Product Development – Engineering / Full time / Hybrid * Scaling open\-weight models without external inference endpoints. * Putting frontier class AI to work across organisations through partnerships with other leading AI startups such as Perplexity. * Increasing operational resiliency for air gapped, on prem, and cloud based systems. * Securing intellectual property and maintaining auditability for high stakes enterprise environments. * Facilitating secure information flow during disaster response, M\&A due diligence, and privileged legal communications. The Role We are looking for an experienced Senior MLOps / LLMOps Engineer to lead the deployment, monitoring, orchestration, and operational reliability of our production LLM applications and agentic AI platform. In this role, you will bridge the gap between AI development and production infrastructure, ensuring multi\-step agentic workflows, data pipelines, and retrieval\-augmented systems run reliably, securely, and at scale within a large\-scale Kubernetes environment. * Design, deploy, and manage LLM services, agentic applications, and supporting AI workloads inside high\-throughput Kubernetes clusters. * Automate containerized deployments, scalable inference endpoints, and blue/green or canary rollout strategies for LLM/Agent releases via modern CI/CD pipelines. * Support and maintain the production operation of agentic AI workflows, including multi\-step tool execution, state management, and multi\-agent coordination. * Rapidly triage and resolve issues across AI application logic, orchestration frameworks, external API integrations, and underlying cloud infrastructure. * Build end\-to\-end monitoring and evaluation (Eval) frameworks to measure and maintain AI output accuracy, drift, latency, cost, and hallucination metrics. * Implement trace\-level observability for agent execution paths (tracking prompts, completions, tool calls, and agent steps). * Monitor and optimize real\-time and batch data pipelines powering AI workloads, including feature stores, vector indexing, and embedding updates. * Manage resource allocation (GPU/CPU utilization), memory footprint, autoscaling strategies, and cloud infrastructure expenditure to optimize time\-to\-first\-token (TTFT) and throughput. What we are looking for: The work we do is vital, but so are the connections that make it happen. We thrive on the shared energy, spontaneous conversations, and mutual trust built when we spend time together. We operate on an office first hybrid model, regularly gathering in our London office to support one another and collaborate. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Work Location: London, ENG, UK Availability: Full time

Job Title: Senior Data Scientist - Product Team Company: MarketCast UK Job Category: Machine Learning Roles & Responsibilities: Role Impact: The Senior Data Scientist \- Product Team plays a pivotal role in designing, developing, and iterating the core machine learning models and analytical frameworks that power MarketCast's commercial product offerings. Operating at the intersection of data science and product development, this individual contributor translates complex mathematical and statistical concepts into scalable, repeatable product features that drive business growth. Daily responsibilities include collaborating closely with product managers, software engineers, and research teams to build robust, production\-grade pipelines and novel methodology layers. By transforming complex, multi\-source datasets into highly reliable, actionable intelligence, this role amplifies the consumer's voice and delivers market\-leading advertising and brand insights to global entertainment and media clients. Product\-Focused Model Development \- The individual designs, builds, and validates advanced statistical models and machine learning algorithms that serve as the core intelligence engine for MarketCast's commercial SaaS offerings. This is achieved by utilizing modern machine learning frameworks such as PyTorch, XGBoost, and LightGBM to process complex consumer datasets. This development ensures that the analytical layer within the products remains robust, highly scalable, and capable of generating precise insights. Working in an embedded product structure, success is measured by the seamless integration and high performance of these models across a diverse range of client use cases. Research Methodology \& Innovation \- The role continuously refines and develops the underlying measurement methodologies and scientific frameworks that differentiate the company's products in the market. This is accomplished by proactively evaluating and introducing cuttingedge techniques, specifically advanced natural language processing (NLP) and Generative AI frameworks. Implementing these advanced approaches ensures that product offerings remain scientifically rigorous, state\-of\-the\-art, and aligned with modern data science practices. The individual collaborates with research insights teams to validate that new methodological approaches directly improve product differentiation and performance. Prototyping \& Experimentation \- The individual leads rapid prototyping initiatives to test, iterate, and validate new modeling approaches and product concepts before full\-scale engineering. This process involves designing and executing rigorous A/B tests, pilot programs, and benchmarking studies. Conducting these experiments mitigates development risk and ensures only high\-performing, mathematically sound methodologies progress to the production pipeline. The candidate partners with engineering and product stakeholders to leverage experimental outcomes, successfully guiding the iterative product development lifecycle. Infrastructure Integration \& MLOps \- This role contributes to the architectural design of scalable data processing workflows and feature engineering pipelines. The candidate collaborates with engineering teams to deploy models using cloud infrastructure, containerization tools, and modern MLOps pipelines. This technical integration ensures that machine learning workflows are highly performant, reliable, and capable of automated monitoring at scale. Success is defined by the creation of stable, production\-grade systems that minimize latency and maintain high model accuracy in real\-world deployment. Quality, Validation \& Standards \- The individual establishes and enforces rigorous standards for model validation, quality assurance, and testing across the entire product development cycle. This is executed by writing clean, testable code and maintaining comprehensive technical documentation for all methodologies. Implementing these strict validation protocols guarantees reproducibility, protects model integrity, and provides a clear foundation for future technical audits. The scientist coordinates with quality assurance and engineering teams to ensure that all deployed data science components consistently meet high accuracy thresholds. Internal Enablement \& Subject Matter Expertise \- The position serves as an internal subject matter expert, explaining the mechanics and commercial value of embedded data science capabilities. This is performed by developing white papers, conducting technical training sessions, and supporting sales enablement activities. Demystifying Mentorship \& Technical Leadership \- The role provides active technical guidance, code reviews, and professional mentorship to junior data scientists within the team. This is delivered by hosting regular knowledge\-sharing sessions, establishing coding standards, and sharing best practices in statistical modeling. Cultivating this collaborative You'll have shaped product roadmaps alongside product managers and engineers, translated business requirements into technical specifications, and acted as the data science voice in cross\-functional decisions. You'll have mentored junior data scientists, run code reviews and knowledge\-sharing sessions, and be comfortable explaining complex methods to commercial and client\-facing audiences through training, white papers or sales support. Take responsibility for outcomes, not just outputs. * Free movie tickets! * 29 days annual leave PLUS Bank Holidays * Flextime with core hours between 10am and 3pm * 2 days’ work from home, per week * 4% match pension scheme * Enhanced maternity pay * Regular social events in both UK locations * Professional growth and career development including LinkedIn Learning GENERAL DATA PROTECTION REGULATION (UK GDPR) NOTICE: The organisation collects and processes personal data relating to its applicants, employees and former employees to manage pre\-employment and employment relationships and post\-employment obligations. The organisation is committed to being transparent about how it collects and uses that data and to meeting its data protection obligations. For further information on the information we collect, how it’s used, and how it's protected, please contact the MarketCast UK HR Team. Work Location: London, ENG, UK Availability: Full time

Job Title: Analytics Engineer (Business Intelligence and Reporting) - Hybrid Company: PH Projects Job Category: Machine Learning Roles & Responsibilities: Key Responsibilities: * Design, develop, and maintain Power BI dashboards, reports, scorecards, and visualisations. * Develop semantic models and reporting datasets that enable trusted self\-service analytics. * Build dashboards and KPI reporting solutions for business stakeholders. * Develop and maintain Power BI Paginated Reports where required. * Assist with optimisation of Power BI models, DAX calculations, and report performance. * Analyse datasets to identify trends, opportunities, risks, and business insights. * Work with business stakeholders to translate requirements into analytical solutions. * Define and maintain business KPIs and performance metrics. * Perform trend analysis and support business investigations through data analysis. * Present findings clearly to both technical and non\-technical stakeholders. * Develop and maintain PySpark notebooks within Microsoft Fabric. * Build reporting\-ready datasets through data cleansing, transformation, and validation. * Develop scalable data models that support reporting and analytics. * Write and optimise complex SQL queries for analytics and reporting. * Work with Lakehouse, Delta Lake, and enterprise data platforms. * Ensure data accuracy and consistency within reporting solutions. * Support data governance and data quality initiatives. * Maintain documentation for datasets, reports, and business rules. * Assist in monitoring and improving data quality processes. * Collaborate with business users, product owners, and technical teams. * Contribute to BI development standards and best practices. * Participate in solution design discussions and continuous improvement initiatives. * Share knowledge and support other team members where appropriate. * KPI Development * Trend Analysis * Data Analysis * Data Storytelling Development Practices* Work Location: Hybrid remote in Pretoria, Gauteng Work Location: Pretoria, GP, South Africa Availability: Full time